This study reports verification results of hindcast data of four systems in the subseasonal-to-seasonal (S2S) prediction project for major stratospheric sudden warmings (MSSWs) in northern winter from 1998/99 to 2012/13. This report deals with average features across all MSSWs, and possible differences between two MSSW types (vortex displacement and split types). Results for the average features show that stratospheric forecast verifications, when further averaged among the four systems, are judged to be successful for lead times around 10 d or shorter. All systems are skillful for lead times around 5 d, whereas the results vary among the systems for longer lead times. A comparison between the MSSW types overall suggests larger forecast errors or lower skill for MSSWs of the vortex split type, although the differences do not have strong statistical significance for almost all cases. This limitation is likely to at least partly reflect the small sample size of the MSSWs available.
基于回报试验结果, 本研究对四个预报系统进行的 1998/99-2012/13 年冬季北半球平流层爆发性增温 (MSSWs) 的次季节至季节预报方案进行了验证. 本研究讨论了所有 MSSWs 的平均特征, 以及两种 MSSWs 类型 (极涡位移型和极涡分裂型) 之间可能存在的差异. 平均特征表明, 当对四个系统的结果进行平均处理时, 可以成功地超前 10 天或更短一点时间的预报 MSSWs. 另外, 每个系统超前 5 天的预报技巧都很高, 但是对于更长的预报时间, 各个系统的预报能力有所不同. 对比不同类型的 MSSWs 的预报结果发现, 对极涡分裂型 MSSWs 的预报会存在较大误差并且预报技巧较低. 所有事件中这些差异在统计检测中并不显著, 这种差异的不显著可能与个例太少有很大的关系.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Andrews, D. G., J. R. Holton, and C. B. Leovy, 1987: Middle Atmosphere Dynamics. Academic Press, 489 pp.
Baldwin, M. P., and T. J. Dunkerton, 2001: Stratospheric harbingers of anomalous weather regimes. Science, 294, 294–581, https://doi.org/10.1126/science.1063315.
Butler, A. H., J. P. Sjoberg, D. J. Seidel, and K. H. Rosenlof, 2017: A sudden stratospheric warming compendium. Earth System Science Data, 9, 9–63, https://doi.org/10.5194/essd-9-63-2017.
Charlton, A. J., and L. M. Polvani, 2007: A new look at stratospheric sudden warmings. Part I: Climatology and modeling benchmarks. J. Climate, 20, 20–449, https://doi.org/10.1175/JCLI3996.1.
Domeisen, D. I. V., and Coauthors, 2019: The role of the stratosphere in subseasonal to seasonal prediction Part I: Predictability of the stratosphere. J. Geophys. Res., https://doi.org/10.1029/2019JD030920.
Karpechko, A. Y., 2018: Predictability of sudden stratospheric warmings in the ECMWF extended-range forecast system. Mon. Wea. Rev., 146, 146–1063, https://doi.org/10.1175/MWR-D-17-0317.1.
Karpechko, A. Y., P. Hitchcock, D. H. W. Peters, and A. Schneidereit, 2017: Predictability of downward propagation of major sudden stratospheric warmings. Quart. J. Roy. Meteorol. Soc., 143, 143–1459, https://doi.org/10.1002/qj.3017.
Kobayashi, S., and Coauthors, 2015: The JRA-55 Reanalysis: General specifications and basic characteristics. J. Meteorol. Soc. Japan, 93, 93–5, https://doi.org/10.2151/jmsj.2015-001.
Lehtonen, I., and A. Y. Karpechko, 2016: Observed and modeled tropospheric cold anomalies associated with sudden stratospheric warmings. J. Geophys. Res., 121, 121–1591, https://doi.org/10.1002/2015JD023860.
Rao, J., R. C. Ren, H. S. Chen, Y. Y. Yu, and Y. Zhou, 2018: The stratospheric sudden warming event in February 2018 and its prediction by a climate system model. J. Geophys. Res., 123, 13332–13345, https://doi.org/10.1029/2018JD028908.
Rao, J., R. C. Ren, H. S. Chen, X. W. Liu, Y. Y. Yu, J. G. Hu, and Y. Zhou, 2019a: Predictability of stratospheric sudden warmings in the Beijing Climate Center Forecast System with statistical error corrections. J. Geophys. Res., 124, 124–8385, https://doi.org/10.1029/2019JD030900.
Rao, J., C. I. Garfinkel, H. S. Chen, and I. P. White, 2019b: The 2019 new year stratospheric sudden warming and its realtime predictions in multiple S2S models. J. Geophys. Res., 124, 11155–11174, https://doi.org/10.1029/2019JD030826.
Scaife, A. A., and Coauthors, 2016: Seasonal winter forecasts and the stratosphere. Atmospheric Science Letters, 17, 17–51, https://doi.org/10.1002/asl.598.
Seviour, W. J. M., D. M. Mitchell, and L. J. Gray, 2013: A practical method to identify displaced and split stratospheric polar vortex events. Geophys. Res. Lett., 40, 5268–5273, https://doi.org/10.1002/grl.50927.
Sigmond, M., J. F. Scinocca, V. V. Kharin, and T. G. Shepherd, 2013: Enhanced seasonal forecast skill following stratospheric sudden warmings. Nature Geoscience, 6, 98–102, https://doi.org/10.1038/ngeo1698.
Taguchi, M., 2014: Predictability of major stratospheric sudden warmings of the vortex split type: Case study of the 2002 Southern event and the 2009 and 1989 Northern events. J. Atmos. Sci., 71, 2886–2904, https://doi.org/10.1175/JAS-D-13-078.1.
Taguchi, M., 2016a: Predictability of major stratospheric sudden warmings: Analysis results from JMA operational 1-month ensemble predictions from 2001/02 to 2012/13. J. Atmos. Sci., 73, 73–789, https://doi.org/10.1175/JAS-D-15-0201.1.
Taguchi, M., 2016b: Connection of predictability of major stratospheric sudden warmings to polar vortex geometry. Atmospheric Science Letters, 17, 17–33, https://doi.org/10.1002/asl.595.
Taguchi, M., 2016c: Features of vortex split MSSWs that are problematic to forecast. Atmospheric Science Letters, 17, 17–517, https://doi.org/10.1002/asl.686.
Taguchi, M., 2018: Comparison of subseasonal-to-seasonal model forecasts for major stratospheric sudden warmings. J. Geophys. Res., 123, 123–10231, https://doi.org/10.1029/2018JD028755.
Tripathi, O. P., A. Charlton-Perez, M. Sigmond, and F. Vitart, 2015a: Enhanced long-range forecast skill in boreal winter following stratospheric strong vortex conditions. Environmental Research Letters, 10, 104007, https://doi.org/10.1088/1748-9326/10/10/104007.
Tripathi, O. P., and Coauthors, 2015b: The predictability of the ex-tratropical stratosphere on monthly time-scales and its impact on the skill of tropospheric forecasts. Quart. J. Roy. Met-eorol. Soc., 141, 141–987, https://doi.org/10.1002/qj.2432.
Vitart, F., and Coauthors, 2017: The Subseasonal to Seasonal (S2S) prediction project database. Bull. Amer. Meteorol. Soc., 98, 98–163, https://doi.org/10.1175/BAMS-D-16-0017.1.
Waugh, D. W., A. H. Sobel, and L. M. Polvani, 2017: What is the polar vortex and how does it influence weather? Bull. Amer. Meteorol. Soc., 98, 37–44, https://doi.org/10.1175/BAMS-D-15-00212.1.
The author thanks those who made the analyzed data available. The JRA-55 data used for this study were provided by the JMA. The JRA-55 data were obtained from the Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory (https://doi.org/10.5065/D6HH6H41). The S2S data were obtained from the ECMWF server (http://apps.ecmwf.int/datasets/data/s2s/). This study was supported by JSPS KAKENHI (Grant No. JP17H01159), and discretionary expense of the President of Aichi University of Education. Comments from two anonymous reviewers improved the manuscript.
• Five-day forecasts (hindcasts) for MSSWs are successful for all four S2S systems of interest when averaged across all 12 (or 10) MSSWs available.
• The success or failure of hindcasts of longer lead times, such as 15 or 20 d, varies among the systems.
• A greater difficulty overall in forecasting vortex-split MSSWs is suggested.
About this article
Cite this article
Taguchi, M. Verification of Subseasonal-to-Seasonal Forecasts for Major Stratospheric Sudden Warmings in Northern Winter from 1998/99 to 2012/13. Adv. Atmos. Sci. 37, 250–258 (2020). https://doi.org/10.1007/s00376-019-9195-6
- major stratospheric sudden warmings
- forecast verification
- subseasonal-to-seasonal prediction project
- vortex displacement and split warmings